Journal of the Korean Society of Safety (한국안전학회지)

The Korean Society of Safety (한국안전학회)
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A Study on a Wearable Smart Airbag Using Machine Learning Algorithm

머신러닝 알고리즘을 사용한 웨어러블 스마트 에어백에 관한 연구

  • Kim, Hyun Sik (Department of Mechanical Design Engineering, Graduate School of Pukyong National University) ;
  • Baek, Won Cheol (Department of Weapon Systems Engineering, Graduate School of Pukyong National University) ;
  • Baek, Woon Kyung (Department of Mechanical Design Engineering, Pukyong National University)
  • 김현식 (부경대학교 기계설계공학과) ;
  • 백원철 (부경대학교 무기체계공학과) ;
  • 백운경 (부경대학교 기계설계공학과)
  • Received : 2019.10.31
  • Accepted : 2020.03.11
  • Published : 2020.04.30
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Abstract

Bikers can be subjected to injuries from unexpected accidents even if they wear basic helmets. A properly designed airbag can efficiently protect the critical areas of the human body. This study introduces a wearable smart airbag system using machine learning techniques to protect human neck and shoulders. When a bicycle accident happens, a microprocessor analyzes the biker's motion data to recognize if it is a critical accident by comparing with accident classification models. These models are trained by a variety of possible accidents through machine learning techniques, like k-means and SVM methods. When the microprocessor decides it is a critical accident, it issues an actuation signal for the gas inflater to inflate the airbag. A protype of the wearable smart airbag with the machine learning techniques is developed and its performance is tested using a human dummy mounted on a moving cart.

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References

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